binGroup2 (version 1.1.0)

summary.gtReg: Summary method for group testing regression model fits

Description

Produce a summary list for objects of class "gtReg" returned by gtReg.

Usage

# S3 method for gtReg
summary(object, ...)

Arguments

object

a fitted object of class "gtReg".

...

currently not used.

Value

summary.gtReg returns an object of class "summary.gtReg", a list containing:

call

the component from object.

link

the component from object.

deviance

the component from object, for simple pooling (type = "sp" in gtReg) only.

aic

the component from object, for simple pooling (type = "sp" in gtReg) only.

df.residual

the component from object, for simple pooling (type = "sp" in gtReg) only.

null.deviance

the component from object, for simple pooling (type = "sp" in gtReg) only.

df.null

the component from object, for simple pooling (type = "sp" in gtReg) only.

deviance.resid

the deviance residuals, for simple pooling (type = "sp" in gtReg) only.

coefficients

the matrix of coefficients, standard errors, z-values, and p-values. Aliased coefficients are omitted.

counts

the component from object.

method

the component from object, for simple pooling (type = "sp" in gtReg) only.

Gibbs.sample.size

the component from object, for array testing (type = "array" in gtReg) only.

cov.mat

the estimated covariance matrix of the estimated coefficients.

Details

The coefficients component of the results gives the estimated coefficients and their estimated standard errors, together with their ratio. This third column is labeled z ratio using Wald tests. A fourth column gives the two-tailed p-value corresponding to the z-ratio based on a Wald test. Note that it is possible that there are no residual degrees of freedom from which to estimate, in which case the estimate is NaN.

See Also

gtReg for creating an object of class "gtReg".

Examples

# NOT RUN {
data(hivsurv)
fit1 <- gtReg(type = "sp", formula = groupres ~ AGE + EDUC., 
              data = hivsurv, groupn = gnum, sens = 0.9, spec = 0.9, 
              method = "Xie")
summary(fit1)

# This examples takes approximately 5 seconds to run.
# 5x6 and 4x5 array
set.seed(9128)
sa2a <- gtSim(type = "array", par = c(-7, 0.1), size1 = c(5, 4), 
              size2 = c(6, 5), sens = 0.95, spec = 0.95)
sa2 <- sa2a$dframe
# }
# NOT RUN {
fit2 <- gtReg(type = "array", formula = cbind(col.resp, row.resp) ~ x, 
              data = sa2, coln = coln, rown = rown, arrayn = arrayn, 
              sens = 0.95, spec = 0.95, linkf = "logit", 
              n.gibbs = 1000, tol = 0.005)
summary(fit2)
# }